We present resolvent-based learning as a new nogood learning method for a distributed constraint satisfaction algorithm. This method is based on a look-back technique in constrain...
Belief revision theory aims to describe how one should change one's beliefs when they are contradicted by newly input information. The guiding principle of belief revision th...
In this paper, we present a new method to design customizable self-evolving fuzzy rule-based classifiers. The presented approach combines an incremental clustering algorithm with a...
Abdullah Almaksour, Eric Anquetil, Solen Quiniou, ...
Abstract. A new dictionary learning method for exact sparse representation is presented in this paper. As the dictionary learning methods often iteratively update the sparse coeffi...
We propose a general method called truncated gradient to induce sparsity in the weights of onlinelearning algorithms with convex loss functions. This method has several essential ...